Computer vision is a growing research field that includes methods for acquiring, processing, analyzing and understanding images. The main driving idea in that field is to duplicate the abilities of human vision by electronically perceiving and understanding images of a scene. Notably, one theme of research in computer vision is the depth perception or, in other words, the three-dimensional (3-D) vision.
Time-Of-Flight (ToF) systems, including a camera and data processing means, appeared recently and are capable of capturing 3-D images of a scene by analysing the time of flight of light from a light source to an object. Such camera systems are used in many applications where depth or distance information from a fixed point is required.
The basic operational principle of a ToF system 3, illustrated by FIG. 1, is to illuminate a scene 15 with a modulated light 16, such as pulses. The modulated light 16 is reflected back from objects within the scene 15 and a lens collects the reflected light 17 and forms an image of objects in the scene on an imaging sensor 35, and in particular, on a sensor plane of the sensor. Depending on the distance of objects from the camera, a delay is experienced between the emission of the modulated light, e.g. pulses, and the reception of their reflection at the camera. For example, an object 2.5 m away from the camera causes a time delay of 16.66 ns. By analysing this delay, and in particular by implementing correlation calculation, the distance of said object from the camera can be retrieved.
The distance of objects from camera can be calculated as follows. For clarity purposes, an example of signals is given FIG. 2. A modulation signal 16 (S) is sent towards an object. After reflection on the object, a signal 17 (Sφ) is detected by a photodetector. This signal Sφ is phase-shifted by a phase φ compared to the original signal S, due to the travelling time.
φ is a key parameter for measuring the distance of objects from camera. To measure this parameter, the photodetected signal Sφ, is usually correlated with electrical reference signals named SI, SĪ, SQ and SQ. SI, SĪ, SQ and SQ are electrical reference signals shifted by 0°, 180°, 90° and 270° respectively, compared to the original optical signal S, as illustrated in FIG. 2. The correlation signals obtained are defined as follows:Sφ,I=Sφ·SI Sφ,Ī=Sφ·SĪSφ,Q=Sφ·SQ Sφ,Q=Sφ·SQ.  (eq. 1-4)Then, two parameters I and Q are calculated such that:I=AS·α·(Sφ,I−Sφ,Ī) andQ=AS·α·(Sφ,Q−Sφ,Q).  (eq. 5-6)AS and α are, respectively, the amplitude change of the photodetected signal Sφ and the efficiency of the correlation.The extraction of φ depends on the shape of the modulation signal S. For example, if S is a sine wave, then
                    φ        =                  {                                                                      arctan                  ⁢                                      Q                    I                                                                                                                    if                    ⁢                                                                                  ⁢                    I                                    ,                                      Q                    ≥                    0                                                                                                                                            arctan                    ⁢                                          Q                      I                                                        +                  π                                                                                                  if                    ⁢                                                                                  ⁢                    I                                    <                  0                                                                                                                          arctan                    ⁢                                          Q                      I                                                        +                                      2                    ⁢                                                                                  ⁢                    π                                                                                                                                          if                      ⁢                                                                                          ⁢                      Q                                        <                    0                                    ,                                      I                    ≥                    0                                                                                                          (                              eq            .                                                  ⁢            7                    ⁢                      -                    ⁢          9                )            Once the phase φ is known, the distance Dφ of objects from camera can be retrieved thanks to the following formula:
                              D          φ                =                              c            ·                          (                              φ                +                                  2                  ⁢                                                                          ⁢                                      π                    ·                    n                                                              )                                            4            ⁢                                                  ⁢                          π              ·                              f                mod                                                                        (                  eq          .                                          ⁢          10                )            where fmod is the modulation frequency and n is a integer number of .
From equations 1-4, one can notice that, in theory, it should be the same signal Sφ which is correlated with reference signals SI, SĪ, SQ and SQ to obtain Sφ,I, Sφ,Ī, Sφ,Q and Sφ,Q, respectively.
In practice, ToF measurements are generally carried out by ToF sensors comprising an array of ToF pixels. In prior art, each of these pixels comprise generally one or two “taps”. A “tap” is a component comprising a control node and a detection region, used to photogenerate charges when exposed to optical signals such as Sφ. The fact of having only one or two taps per pixel involves that, in practice, the measure of Sφ is time-sequential. For example, a pixel comprising only one tap has to measure successively 4 distinct signals, Sφ 1-4, in order to calculate I, Q and then Dφ. In these configurations, several exposures occur and, if in between each exposure the object has moved, then the depth data Dφ is corrupted.
The fact of using only one or two taps per pixel is problematic for matters of consistency of the depth calculation, but not only. It is also problematic for design reasons. Indeed, if several distinct signals Sφ i are measured, a memory has to be added in pixels, on the sensor or on a system level in order to store the signals Sφ i before calculation steps. The size of ToF systems is then dramatically increased.
Finally, when several taps are comprised in a single pixel, the driving signals used to drive them are often not optimal as the bandwidth required is too high. When a positive potential is applied to a tap with respect to the other taps, the tap is activated and the detectivity is high, meaning the detection region of the activated tap will be receiving the majority of the photogenerated minority carriers in the pixel. With a 4-tap pixel architecture, a straightforward approach is to enable each of the four taps for 25% of the modulation period, as illustrated in FIG. 3. For a sent modulated signal with frequency 50 MHz, the 4-tap device taps will need a response time equivalent to 100 MHz due to the 25% duty cycle of each tap.
Despite what has been presented in prior art, a method and a system remain to be proposed in order to measure non-biased distances of object from ToF system while reducing both the size of the ToF systems and the bandwidth required for the taps.